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I was interviewed in Jan 2025.
I was interviewed in Jan 2025.
Introduction regarding the subject, questions related to several programming languages.
Work Projects, the output generated from the following projects and their industrial purpose
Aptitude Round, along with some technical and non-technical questions
Share my precious project details.
Unified Mentor interview questions for designations
I applied via LinkedIn and was interviewed in Mar 2024. There were 2 interview rounds.
Just need to answer some coding questions
Python Assignments for numpy pandas
Top trending discussions
I applied via Campus Placement and was interviewed in Nov 2024. There were 3 interview rounds.
There were verbal, non verbal, reasoning , English and maths questions
I worked on a project analyzing customer behavior using machine learning algorithms.
Used Python for data preprocessing and analysis
Implemented machine learning models such as decision trees and logistic regression
Performed feature engineering to improve model performance
Proficient in Python, R, and SQL with experience in data manipulation, visualization, and machine learning algorithms.
Proficient in Python for data analysis and machine learning tasks
Experience with R for statistical analysis and visualization
Knowledge of SQL for querying databases and extracting data
Familiarity with libraries such as Pandas, NumPy, Matplotlib, and Scikit-learn
I currently stay in an apartment in downtown area.
I stay in an apartment in downtown area
My current residence is in a city
I live close to my workplace
I am a data science enthusiast with a strong background in statistics and machine learning.
Background in statistics and machine learning
Passionate about data science
Experience with data analysis tools like Python and R
I applied via Campus Placement
Basic DSA questions will be asked Leetcode Easy to medium
BERT is faster than LSTM due to its transformer architecture and parallel processing capabilities.
BERT utilizes transformer architecture which allows for parallel processing of words in a sentence, making it faster than LSTM which processes words sequentially.
BERT has been shown to outperform LSTM in various natural language processing tasks due to its ability to capture long-range dependencies more effectively.
For exa...
Multinomial Naive Bayes is a classification algorithm based on Bayes' theorem with the assumption of independence between features.
It is commonly used in text classification tasks, such as spam detection or sentiment analysis.
It is suitable for features that represent counts or frequencies, like word counts in text data.
It calculates the probability of each class given the input features and selects the class with the
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